Research And Application Of Social Network Users In The Trust Relationship

The proliferation of web-based social networks has lead to new innovations in social networking, particularly by allowing users to describe their relationships beyond a basic connection. In this dissertation, I look specifically at trust in web-based social networks, how it can be computed, and how it can be used in applications. I begin witn a definition of trust and a description of several properties that affect how it is used in algorithms.The computational problem of trust is to determine how much one person in the network should trust another person to whom they are not connected. I present two sets of algorithms which were much used for calculating these trust inferences. Then I give a modified algorithm and confirm this algorithm can make more accuracy recommendations for users than other algorithms using experimentation.Collaborative filtering is the most popular approach to build recommender systems and has been successfully employed in many applications. However, it cannot prevent deception and insincerity. In addition, these methods do not know how confident they are in their recommendations. Empirical investigations on the correlation of interpersonal trust and interest similarity provide the component glue that melds these results together and renders the eventual creation of a recommender framework feasible, and then finds the recommendations becoming more accuracy.